---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: IndicBERTv2-MLM-only-indic_glue
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# IndicBERTv2-MLM-only-indic_glue

This model is a fine-tuned version of [ai4bharat/IndicBERTv2-MLM-only](https://huggingface.co/ai4bharat/IndicBERTv2-MLM-only) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1941
- Precision: 0.8410
- Recall: 0.8738
- F1: 0.8571
- Accuracy: 0.9427

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.5734        | 0.31  | 200  | 0.2794          | 0.7618    | 0.7979 | 0.7794 | 0.9103   |
| 0.2767        | 0.62  | 400  | 0.2182          | 0.8139    | 0.8361 | 0.8248 | 0.9300   |
| 0.218         | 0.94  | 600  | 0.2058          | 0.8167    | 0.8648 | 0.8401 | 0.9365   |
| 0.1758        | 1.25  | 800  | 0.1995          | 0.8311    | 0.8641 | 0.8473 | 0.9380   |
| 0.1366        | 1.56  | 1000 | 0.1928          | 0.8430    | 0.8695 | 0.8561 | 0.9417   |
| 0.1349        | 1.88  | 1200 | 0.1941          | 0.8410    | 0.8738 | 0.8571 | 0.9427   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3